Epileptic Seizure Detection Using Probability Distribution Based On Equal Frequency Discretization
Yazarlar (3)
Çukurova Üniversitesi, Türkiye
Prof. Dr. Mahmut HEKİM
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Bülent Ecevit Üniversitesi, Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Journal of Medical Systems |
| Dergi ISSN | 0148-5598 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q4 |
| Makale Dili | İngilizce |
| Basım Tarihi | 08-2012 |
| Cilt No | 36 |
| Sayı | 4 |
| Sayfalar | 2219 / 2224 |
| DOI Numarası | 10.1007/s10916-011-9689-y |
| Makale Linki | http://link.springer.com/10.1007/s10916-011-9689-y |
| Özet |
| In this study, we offered a new feature extraction approach called probability distribution based on equal frequency discretization (EFD) to be used in the detection of epileptic seizure from electroencephalogram (EEG) signals. Here, after EEG signals were discretized by using EFD method, the probability densities of the signals were computed according to the number of data points in each interval. Two different probability density functions were defined by means of the polynomial curve fitting for the subjects without epileptic seizure and the subjects with epileptic seizure, and then when using the mean square error criterion for these two functions, the success of epileptic seizure detection was 96.72%. In addition, when the probability densities of EEG segments were used as the inputs of a multilayer perceptron neural network (MLPNN) model, the success of epileptic seizure detection was 99.23%. This results show that non-linear classifiers can easily detect the epileptic seizures from EEG signals by means of probability distribution based on EFD. © 2011 Springer Science+Business Media, LLC. |
| Anahtar Kelimeler |
| Curve fitting | EEG signals | Epileptic seizure detection | Equal frequency discretization (EFD) | Mean square error (MSE) | Multilayer perceptron neural network (MLPNN) | Probability distribution |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 20 |
| SCOPUS | 23 |
| Google Scholar | 36 |